The incidence of carcinoid cancers, in particular those of the small intestine, have increased four-fold over the past 30 years. Unfortunately, the majority of these small intestinal carcinoid cancers (SICC) are diagnosed with advanced disease where prognosis is poor. Diagnosis is often missed or delayed by nearly 10 years because symptoms are ambiguous. These cancers have a major hereditary component, much of which is not explained by the rare genetic syndromes. First-degree relatives of SICC cases have an approximately 10-fold relative risk of developing SICC. Interestingly the risk to siblings is double that to parents which suggests that some aspect of a shared environment compounds the risk of developing SICCs. We hypothesize that environmental exposures and inherited genetic factors contribute to the development of small intestinal carcinoid cancers and that the interaction of these two components drives penetrance. We have the unique opportunity to use a one-of-a-kind resource to investigate environmental exposures AND inherited genetic risk factors which contribute to the development of SICCs. The resource we will use is the Utah Population Database (UPDB), a computerized integration of 7 million individuals and genealogies dating back to the 1800s. This is overlaid with statewide vital statistics, SEER cancer records, medical records, and public records. UPDB is recently expanded to include geo-spatial and environmental data to promote epidemiological research and gain insights into gene-environment interactions. This exploratory project will set the stage for future epidemiological research using this powerful resource. The aims of this proposal are as follows. 1. To identify genetic variants that explain high-risk familial SICC. We have identified 20 large multi-generation pedigrees with 3 to 7 SICC cases and statistical excess of SICC. Cases and family members will be enrolled in research, focusing on families with highest excess risk. DNA from blood and archived tumor/tissue blocks will be obtained. Whole genome sequencing will be applied to affected individuals in these large extended pedigrees to identify genetic variants predicted to be responsible for familial SICC. 2. To model environmental risk profiles of SICC using geo-coding, place and time of residence, and environmental exposure data. Using historical residential addresses from public resources, we can identify when, how long, and where each individual in our cohort of 666 SICCs resided. Follow up data extends for a median of 50 years these cases. Environmental exposure data such as source of drinking water, hazardous pollutants, or agricultural pesticide use, is overlaid on the time and space to assign exposures on an individual level and test for exposures that underlie increased risk of SICC. Finally, we will join the efforts of Aim 1 and 2 to pursue an exploratory aim to model main effects of environmental exposures with familial clustering to define potential gene-environment interactions for SICC risk. Understanding these genetic and environmental risk factors is important to allow for prevention, targeted screening of at-risk individuals, earlier diagnosis and better survival.